Recently, a technique called big data analysis to create new values by analyzing an enormous amount of data relating to the social infrastructure such as social working services, finance, medical services, and traffic has been being put into practical use.
Regarding the big data analysis, capacities of both input data collected from the social infrastructure and output data which are analysis results are very large and such capacities as well as time continue to increase.
For example, this problem is apparent when the big data analysis is performed by using a cloud service. Computation resources for the cloud service are calculated based on performance and operating time of computers and storage resources are often calculated based on a data capacity and a recording time period. Accordingly, as the data capacity expands, usage fees for the storage resources become dominant over those for the computation resources with respect to the total cost. Therefore, when the big data analysis is performed by using the cloud service, the usage cost of the cloud service becomes enormous.
As a technique to inhibit an increase of data capacity in a storage apparatus, there is a technique called information life cycle management (ILM: Information Lifecycle Management) to migrate low-value data to an inexpensive device or delete such data based on time elapsed from the generation of the data or access frequency to the data (see Patent Literature 1).